Day 1: GPU Technology Conference

The GPU Technology Conference started up Tuesday with a rousing keynote by Nvidia CEO Jen-Hsun Huang. The room was largely filled with developers, and Huang’s message that MATLAB, Ansys, and Amber HPC applications are all now running on the Tesla GPU platform was well received.

With demos that spanned from to real-time rendering to automotive design to robotic heart surgery, Huang did a great job of focusing his talk not on technology, but on how people are using GPUs to “change the world.” There are literally hundreds of millions GPUs out there in the wild, and I think the democratization of parallel HPC computing is here thanks to CUDA and some very smart technology bets made by Nvidia.

Don’t kid yourself. GPUs are a game-changer.” said Frank Chambers, a GTC conference attendee shopping for GPUs for his finite element analysis work. “What we are seeing here is like going from propellers to jet engines. That made transcontinental flights routine. Wide access to this kind of computing power is making things like artificial retinas possible, and that wasn’t predicted to happen until 2060.”

This conference has been a pleasant surprise for me in a number of ways. It’s only in it’s second year, yet the remarkable growth and energy here is notable:

More than 140 press and industry analysts

Four times the response to call for talks

Twice the number of talks, up to nearly 300 hours

Twice the number of products and technology being demo’ed

Several thousand attendees from 50+ countries

Researchers/scientists from 200+ universities, national labs and govt agencies

Nearly 100 CEO/CTOs

I think we are witnessing the birth of a new computing ecosystem here. The exhibitors are incredibly enthusiastic and have great demos to show. Today’s news may not seem like a big deal at first look, but, as one speaker said today, the porting of MATLAB opens up GPU computing to anyone who knows math. To me, that adds up to a rising groundswell.

Comments

At AccelerEyes, we are happy that MathWorks has finally turned the corner on accepting GPU technology, something we’ve been pushing them to do since 2007.

We are also excited, because this is great news for the GPU computing ecosystem, to see one of the technical computing giants validate the approach we’ve been delivering with Jacket.

Finally, we are thrilled, because we are confident that anyone attempting to use GPU computing via MATLAB directly will end up becoming a Jacket programmer (for instance, try indexing into a matrix or running a convolution with R2010b). To see how Jacket stacks up against the alternative, see:

Jacket will always offer the best in GPU computing technology. Without Jacket’s runtime technology, no MATLAB GPU computing attempt will be able to come close to competing in performance benefits on real applications. It is one thing to get a few functions to run on the GPU. But getting full applications to run fast on the GPU is an entirely different matter.

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